Document Detail


Binomial regression in GLIM: estimating risk ratios and risk differences.
MedLine Citation:
PMID:  3509965     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Although an estimate of the odds ratio adjusted for other covariates can be obtained by logistic regression, until now there has been no simple way to estimate other interesting parameters such as the risk ratio and risk difference multivariately for prospective binomial data. These parameters can be estimated in the generalized linear model framework by choosing different link functions or transformations of binomial or binary data. Macros for use with the program GLIM provide a simple method to compute parameters other than the odds ratio while adjusting for confounding factors. A data set presented previously is used as an example.
Authors:
S Wacholder
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  American journal of epidemiology     Volume:  123     ISSN:  0002-9262     ISO Abbreviation:  Am. J. Epidemiol.     Publication Date:  1986 Jan 
Date Detail:
Created Date:  1986-01-21     Completed Date:  1986-01-21     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  7910653     Medline TA:  Am J Epidemiol     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  174-84     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Biometry*
Computers*
Epidemiologic Methods*
Female
Humans
Infant, Low Birth Weight
Infant, Newborn
Pregnancy
Regression Analysis
Smoking
Social Class
Comments/Corrections
Comment In:
Am J Epidemiol. 1989 Nov;130(5):1065   [PMID:  2816893 ]

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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